Global transcriptomic analysis of a murine osteocytic cell line subjected to spaceflight
Bibliographic record
Abstract
Bone loss is a major health concern for astronauts during long-term spaceflight and for patients during prolonged bed rest or paralysis. Growing evidence suggests that osteocytes, the most abundant cells in the mineralized bone matrix, play a key role in sensing mechanical forces applied to the skeleton and integrating the orchestrated response into subcellular biochemical signals to modulate bone homeostasis. However, the precise molecular mechanisms underlying both mechanosensation and mechanotransduction in late-osteoblast-to-osteocyte cells under microgravity (µG) have yet to be elucidated. To unravel the mechanisms by which late osteoblasts and osteocytes sense and respond to mechanical unloading, we exposed the osteocytic cell line, Ocy454, to 2, 4, or 6 days of µG on the SpaceX Dragon-6 resupply mission to the International Space Station. Our results showed that µG impairs the differentiation of osteocytes, consistent with prior osteoblast spaceflight experiments, which resulted in the downregulation of key osteocytic genes. Importantly, we demonstrate the modulation of critical glycolysis pathways in osteocytes subjected to microgravity and discovered a set of mechanical sensitive genes that are consistently regulated in multiple cell types exposed to microgravity suggesting a common, yet to be fully elucidated, genome-wide response to microgravity. Ground-based simulated microgravity experiments utilizing the NASA rotating-wall-vessel were unable to adequately replicate the changes in microgravity exposure highlighting the importance of spaceflight missions to understand the unique environmental stress that microgravity presents to diverse cell types. In summary, our findings demonstrate that osteocytes respond to µG with an increase in glucose metabolism and oxygen consumption.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".